Changyong Shu

Computer Vision and Pattern Recognition · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 207 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 74 citations into it; #17,699 of 21,575 by trust here, #16,367 by citations
• Artificial Intelligence — 53 citations into it; #28,992 of 35,345 by trust here, #25,040 by citations
• Model Architectures — 10 citations into it
• Optimization & Training — 7 citations into it

Whom Changyong Shu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ross B. Girshick
5. Yoshua Bengio
6. Shaoqing Ren
7. Jimmy Ba
8. Yann LeCun
9. Diederik P. Kingma
10. X. Zhang

Who trusts Changyong Shu overall

1. Juan R. Terven
2. Lin Wang
3. Diana-Margarita Córdova-Esparza
4. Zhendong Yang
5. Tao Huang
6. Kuk-Jin Yoon
7. Chuyin Li
8. Ailing Zeng

Papers from Changyong Shu's perspective

Ordered by how strongly the researchers Changyong Shu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Channel-wise Knowledge Distillation for Dense Prediction* (2020) — 462 citations
• Knowledge Squeezed Adversarial Network Compression (2019) — 12 citations